mloss.org Indefinite Core Vector Machinehttp://mloss.orgUpdates and additions to Indefinite Core Vector MachineenFri, 05 Jan 2018 22:35:38 -0000Indefinite Core Vector Machine 0.1http://mloss.org/software/view/702/<html><p>Indefinite learning problems occur frequently if non-metric proximity
measures are used (some neural network kernels, dynamic timewarping measures, alignment functions, inner distance and many other).
The respective (supervised) learning algorithms have often
quadratic to cubic complexity and a non-sparse decision function.
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<p>In this library a KrÄ•in space Core Vector Machine (iCVM) solver is derived. A sparse model with linear runtime complexity
can be obtained under a low rank assumption. The obtained iCVM models can be applied to indefinite kernels without additional preprocessing. Using iCVM one can solve CVM with usually troublesome kernels having large negative eigenvalues or large numbers of negative eigenvalues.
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<p>In addition to the referenced paper the code provides an effective sparsification approach such that the final model is sparse again.
</p></html>frank michael schleif,peter tinoFri, 05 Jan 2018 22:35:38 -0000http://mloss.org/software/rss/comments/702http://mloss.org/software/view/702/large scalesupervised learningnon mercerindefinite kernelscore vector machine